Gated Recurrent Unit

GRU – Gated Recurrent Unit Architecture

The foundational structure of the Gated Recurrent Units (GRUs) represents a recurrent neural network (RNN) architecture utilized within the realm of deep learning and also provides an enhanced computational advantage over the Long Short-Term Memory (LSTM), affording it a distinct preference in specific domains.

Deep Learning – Introduction to Artificial Neural Networks

LSTM – Long Short Term Memory Architecture

LSTM is used to solve issues with RNNs processing extensive sequential data. Calling LSTM as an advanced RNNs is not wrong. LSTMs excel in processing sequential data with long-term dependencies. LSTM is utilized for tasks like sentiment analytics, language generation, speech recognition, and video analysis.